An integrated microtechnology platform for spatially resolved mass spectrometry-based proteomics

用于基于空间分辨质谱的蛋白质组学的集成微技术平台

• 批准号: 10564117
• 负责人: Sindy Kam-Yan Tang
• 金额: $ 63.98万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-01-06 至 2027-12-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10564117
• 关键词: Acceleration; Address; Antibodies; Biological; Biomedical Research; Cancer Biology; Cell physiology; Cells; Couples; Data; Development; Devices; Diagnosis; Disease; Dissection; Early Diagnosis; Ethanol; Extracellular Protein; Functional disorder; Goals; Heterogeneity; Human; Immunosuppression; Intervention; Label; Liquid Chromatography; Manuals; Maps; Mass Spectrum Analysis; Measures; Methods; Microdissection; Microfluidic Microchips; Microfluidics; Molecular; Neoplasm Metastasis; Outcome; Pathology; Pathway interactions; Pharmaceutical Preparations; Play; Post-Translational Protein Processing; Preparation; Process; Proteins; Proteome; Proteomics; Publishing; RNA; Resolution; Role; Running; Sampling; Site; Slice; Spatial Distribution; Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization; Technology; Tissue Preservation; Tissues; Tumor Tissue; Work; biomarker identification; cancer initiation; clinical diagnostics; design; fabrication; imaging approach; innovation; innovative technologies; laser capture microdissection; mass spectrometric imaging; meter; nano; nanoDroplet; nanofabrication; new technology; new therapeutic target; novel; novel marker; novel therapeutic intervention; preservation; protein biomarkers; response; skin squamous cell carcinoma; spatial integration; tandem mass spectrometry; technology platform; therapeutic target; tissue fixing; tissue mapping; transcriptomics; tumor; tumor heterogeneity; tumor initiation; tumor microenvironment; tumor progression

Project Summary The spatial organization of cells and molecules in biological tissues plays a critical role in pathophysiology. For example, spatial heterogeneity in the tumor microenvironment determines tumor initiation, metastasis, and drug response. Despite advances in spatial transcriptomics to map RNA in tissues, it is proteins, rather than RNA, that drive most cellular processes and determine disease state. As protein abundance cannot be inferred precisely from transcriptomic data, it is important to measure protein abundance and their spatial distribution to better predict pathophysiological phenomena, as well as to identify biomarkers and therapeutic targets. Previous work on spatial proteomics is based on antibody recognition, mass spectrometry imaging, or physical dissection of the tissue followed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). Antibody-based and mass spectrometry imaging approaches have low proteome coverage (<100 proteins). The only approach with deep coverage (>3000 proteins) is tissue dissection followed by LC-MS/MS. This method leverages the power of state-of-the-art LC-MS/MS to achieve in-depth quantification of thousands of proteins along with their post-translational modifications. However, this approach is limited by current dissection methods. Manual dissection has low throughput and poor spatial resolution. Laser capture microdissection (LCM) has high resolution, but the isolation of many pixels, required for tissue mapping, is tedious and suffers from sample loss. The goal of this project is to develop a high throughput and scalable technology to perform tissue microdissection that preserves tissue spatial information and couples directly to established LC-MS/MS workflow for deep and unbiased spatial mapping of the proteome. We will demonstrate our technology on tumor slices of cutaneous squamous cell carcinoma. Our approach integrates a novel tissue micro-dicing device (“µDicer”), a nanodroplet sample preparation platform (“nanoPOTS”) for LC-MS/MS analysis with single-cell sensitivity, and a microfluidic device (“µMapper”) to transfer the diced tissue pixels from the µDicer to the nanoPOTS array while preserving their spatial order. Our approach is innovative because no technology currently exists to perform tissue micro-dissection and their transfer to macroscopic wells in parallel for LC-MS/MS while preserving spatial information. The specific aims are to optimize the µDicer for dicing fixed tissue slices into 10-100 µm micro-tissue pixels, develop and validate the µMapper to transfer tissue pixels from the µDicer onto nanoPOTS chips, and develop a high throughput and integrated spatial proteomics workflow and apply it to map human tumor slices. The project is significant because it will accelerate mass spectrometry-based spatial proteomics, thereby advancing our understanding of the role of tissue heterogeneity in pathophysiology, such as the role of the tumor microenvironment on cancer progression, and will enable the identification of novel protein biomarkers and therapeutic targets to facilitate the early detection, diagnosis, and intervention of diseases.

项目概要 生物组织中细胞和分子的空间组织在病理生理学中起着至关重要的作用。 例如，肿瘤微环境的空间异质性决定肿瘤的发生、转移和药物 尽管在绘制组织中 RNA 的空间转录组学方面取得了进展，但它是蛋白质，而不是 RNA， 驱动大多数细胞过程并确定疾病状态，因为蛋白质丰度无法推断。 准确地根据转录组数据，测量蛋白质丰度及其空间分布对于 更好地预测病理生理现象，以及识别生物标志物和治疗靶点。 先前关于空间蛋白质组学的工作基于抗体识别、质谱成像或 对组织进行物理解剖，然后进行液相色谱-串联质谱 (LC-MS/MS)。 基于抗体和质谱成像方法的蛋白质组覆盖率较低（<100 个蛋白质）。 唯一深度覆盖（> 3000 个蛋白质）的方法是组织解剖，然后进行 LC-MS/MS。 利用最先进的 LC-MS/MS 的力量实现数千种蛋白质的深度定量 然而，这种方法受到当前解剖方法的限制。 手动解剖的通量低，空间分辨率差，激光捕获显微切割（LCM）的分辨率高。 分辨率，但组织映射所需的许多像素的隔离是乏味的，并且会导致样本丢失。 该项目的目标是开发一种高通量和可扩展的技术来执行组织 显微切割可保留组织空间信息并直接耦合到已建立的 LC-MS/MS 工作流程 我们将展示我们在肿瘤切片上的技术。 我们的方法集成了一种新型组织微切割装置（“μDicer”），一种 用于具有单细胞灵敏度的 LC-MS/MS 分析的纳米液滴样品制备平台（“nanoPOTS”），以及 微流体装置（“μMapper”）将切块的组织像素从μDicer传输到nanoPOTS阵列，同时 我们的方法是创新的，因为目前还没有技术可以执行。 组织显微解剖及其并行转移至宏观孔以进行 LC-MS/MS，同时保留空间 具体目标是优化 µDicer，将固定组织切片切成 10-100 µm 的微组织。 像素，开发并验证 µMapper 以将组织像素从 µDicer 转移到 nanoPOTS 芯片上，以及 开发高通量和集成的空间蛋白质组学工作流程，并将其应用于绘制人类肿瘤切片图。 该项目意义重大，因为它将加速基于质谱的空间蛋白质组学，从而 增进我们对组织异质性在病理生理学中的作用的理解，例如肿瘤的作用 微环境对癌症进展的影响，并将能够识别新的蛋白质生物标志物和 旨在促进疾病的早期发现、治疗诊断和干预。